One of the most important global phenomena that are currently threatening the ecosystem is land degradation and is mainly caused by the climatic changes and human influence. Land degradation is the reduction in the capability of the land to produce benefits from a particular land use under a specified form of land management. Land degradation is the consequence of important processes, which is active in arid and semi-arid ecosystems, where water is the original limiting factor in execution of land application. Remotely sensed data provide timely, accurate and reliable information on degraded lands at definite time intervals in a cost effective manner. In this research, the TM/ETM+ images were used to study changes occurred in the first decade of the new millennium; May 2001 to April 2011. In the present study, efforts have been made to identify and map areas affected by land degradation in Kot Addu tehsil of Muzaffargarh, Punjab province, Pakistan. The Normalized Difference Vegetation Index (NDVI), change detection technique was applied upon TM/ETM+ images and further unsupervised classification was used for extraction of information regarding the desert, bare soil, cultivatable land and cultivated land. The NDVIs properties help mitigate a large part of the variations that result from the overall remotesensing system. The result shows that the desert is 458.73 km2 (17%), bare soil is 1160.33 km2 (43%), cultivated land is 647.62 km2 (24%) and cultivatable land is 431.75 km2 (16%) in April 2011. The values of the Kappa statistics were used to compare the performance of the classifiers. The data sets were analyzed using ArcGIS software in the Geographic Information System environment and can be implemented in the drylands of Pakistan.